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Research questionHow can streaming PCA recover principal components when the data covariance changes over time?Streaming PCA processes observations sequentially, but the covariance governing those observations may change rather than remain fixed. This makes it unclear when principal-component estimates can converge and how quickly.
Machine Learning
Statistical Machine Learning
Latest papersRecent research connected to this question, newest first.Robust Streaming PCAThe setting models the covariance matrix as belonging to a temporal uncertainty set. The evidence covers fundamental convergence limits and analyses of the noisy power method and Oja’s algorithm, supported by experiments on synthetic and real-world datasets.research paper · Sep 2, 2026
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